In recent years, as social demands for information offering services to drivers have been increased replenishment of a transportation control system to support such services has been required. Especially, there is a need to improve the function of a traffic flow change monitoring system for grasping changes in traffic flow more rapidly and more accurately.
The conventional traffic flow change monitoring system will now be explained on the basis of the drawings.
FIG. 5 is a block diagram showing the construction of the conventional traffic flow change monitoring system.
In FIG. 5, reference numeral 1 designates vehicle perceiving sensors such as ultrasonic sensors placed on a road, numeral 2 designates a signal detection section for detecting vehicle perception signals from the vehicle perceiving sensors 1, and numeral 3 designates a vehicle perception data compiling section for compiling the vehicle perception signals detected by the signal detection section 2 as a parameter such as a vehicle speed.
Numeral 4 designates a vehicle perception data classification section which ranks vehicle perception data compiled by the vehicle perception data compilation section 3 by means of predetermined threshold values concerning vehicle perception data.
Numeral 5 designates a change judgement section which judges a change in traffic flow by monitoring a time-dependent change of the result of ranking of the vehicle perception data by the vehicle perception data classification section 4. Numeral 6 designates an output section for outputting the result of judgement by the change judgement section 5.
Next, explanation will be made of the operation of the above-mentioned conventional system.
When a vehicle running on a road passes a perception range of the vehicle perception sensor 1, the signal perception section 2 detects the passage of the vehicle as a vehicle perception signal. This vehicle perception signal is compiled in the vehicle perception data compilation section 3 as a parameter such as a pulse indicative of a signal detecting time corresponding to the speed of the vehicle and the compiled vehicle perception data is sent to the vehicle perception data classification section 4 in a block at every unit time.
In the vehicle perception data classification section 4, the predetermined threshold values and parameterized vehicle perception data are compared to classify the individual vehicle perception data. The result of classification is sent to the change judgement section 5 which in turn monitors a time-dependent change of the result of classification of the vehicle perception data at a same measuring spot to judge a change in traffic flow. The result of judgement is outputted from the output section 6.
In this manner, even the above-mentioned conventional traffic flow measuring system can monitor a change in traffic flow by processing vehicle perception signals obtained from the vehicle perceiving sensors.
However, in the above-mentioned conventional traffic flow monitoring system, since the change in traffic flow is monitored in accordance with the speed or the like of individual vehicles, it is not possible to monitor a positional relationship between successively running vehicles. Accordingly, there is a problem that it is not possible to make a prompt forecast of occurrence and dissolution of a traffic congestion and to make a prompt detection of an unexpected event such as an accident.
An object of the present invention is to solve the above problem in the prior art and to provide an excellent traffic flow change monitoring system which is capable of promptly and accurately detecting a change in traffic flow.